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arXiv · 2303.16328

Worst case tractability of linear problems in the presence of noise: linear information

Leszek Plaskota·Paweł Siedlecki
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Abstract

We study the worst case tractability of multivariate linear problems defined on separable Hilbert spaces. Information about a problem instance consists of noisy evaluations of arbitrary bounded linear functionals, where the noise is either deterministic or random. The cost of a single evaluation depends on its precision and is controlled by a cost function. We establish mutual interactions between tractability of a problem with noisy information, the cost function, and tractability of the same problem, but with exact information.

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Leszek Plaskota, Paweł Siedlecki. 2023-03-28. Worst case tractability of linear problems in the presence of noise: linear information. https://arxiv.org/abs/2303.16328

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